ClusterR

Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, doi:10.18637/jss.v001.i04; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, doi:10.1145/1772690.1772862; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, doi:10.21105/joss.00026; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, doi:10.1126/science.1136800.

Last 30 days

This package has been downloaded 4,135 times in the last 30 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 144 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 60,152 times in the last 365 days. This work is reaching a lot of screens. A significant achievement indeed! The day with the most downloads was Jun 18, 2024 with 425 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.